library(tidyverse)
library(plotly)

datalog <- read_csv("../../data/DATALOG_FLIGHT (1).TXT")
dat <- datalog %>%
  select(`Sample Number`, `Nanolab elapsed time (ms)`, `NR exptime (s)`, `X Acceleration (G)`, `Y Acceleration (G)`, `Z Acceleration (G)`, `Flight Altitude (ft)`, `Flight State`) %>% 
  map(., as.numeric)

dat <- as.data.frame(dat)

#colnames(dat)

dat <- dat %>% 
  mutate(total_gs = (abs(X.Acceleration..G.) + abs(Y.Acceleration..G.) + abs(Z.Acceleration..G.)))

Questions

dat %>% 
  #filter(Flight.Altitude..ft. > 0) %>% 
  #filter(Sample.Number > 1000) %>% 
  ggplot(aes(x = `Sample.Number`, y = `Flight.Altitude..ft.`, color = total_gs)) +
  geom_point() +
  theme_bw()

dat %>% 
  #filter(Flight.Altitude..ft. > 0) %>% 
  ggplot(aes(x = Flight.Altitude..ft., y = total_gs, color = Sample.Number)) +
  geom_point() +
  theme_bw()

What? Lets look at depth.

fig <- plot_ly(dat, 
               x = ~Sample.Number, 
               y = ~Flight.Altitude..ft., 
               z = ~total_gs, 
               color = ~Sample.Number) %>% 
  add_markers() %>% 
  layout(scene = list(xaxis = list(title = "Sample Number"),
                      yaxis = list(tilte = "Altitude"),
                      zaxis = list(title = "Total G's")))

fig
fig <- plot_ly(dat, 
               x = ~X.Acceleration..G., 
               y = ~Y.Acceleration..G., 
               z = ~Z.Acceleration..G., 
               color = ~total_gs) %>% 
  add_markers() %>% 
  layout(scene = list(xaxis = list(title = "X"),
                      yaxis = list(tilte = "Y"),
                      zaxis = list(title = "Z")))

fig